Contingency-theorists have gestured to a series of phenomena such as random mutations or rare Armageddon-like events as that which accounts for evolutionary contingency. These phenomena constitute a class, which may be aptly called the ‘sources of contingency’. In this paper, I offer a probabilistic conception of what it is to be a source of contingency and then examine two major candidates: chance variation and genetic drift, both of which have historically been taken to be ‘chancy’ in a number of different senses. However, contra the gesturing of contingency-theorists, chance variation and genetic drift are not always strong sources of contingency, as they can be non-chancy (and hence, directional) in at least one sense that opposes evolutionary contingency. The probabilistic conception offered herein allows for sources of contingency to appropriately vary in strength. To this end, I import Shannon’s information entropy as a statistical measure for systematically assessing the strength of a source of contingency, which is part and parcel of identifying sources of contingency. In brief, the higher the entropy, the greater the strength. This is also empirically significant because molecular, mutational, and replicative studies often contain sufficient frequency or probability data to allow for entropies to be calculated. In this way, contingency-theorists can evaluate the strength of a source of contingency in real-world cases. Moreover, the probabilistic conception also makes conceptual room for the converse of sources of contingency: ‘sources of directionality’, which ought to be recognised, as they can interact with genuine sources of contingency in undermining evolutionary contingency.

中文翻译：

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进化偶然性的来源：机会变异和遗传漂变

偶然性理论家已经指出了一系列现象，例如随机突变或罕见的世界末日之类的事件，作为解释进化偶然性的因素。这些现象构成了一个类，可以恰当地将其称为“偶然性的来源”。在这篇论文中，我提供了一个关于什么是偶然性来源的概率概念，然后研究了两个主要的候选者：机会变异和遗传漂变，这两者在历史上都被认为是在许多不同意义上的“偶然性” . 然而，与偶然性理论家的姿态相反，偶然性变异和遗传漂变并不总是偶然性的强大来源，因为它们至少在一种反对进化偶然性的意义上可能是非偶然性的（因此是定向的）。此处提供的概率概念允许意外事件的来源在强度上适当变化。为此，我将香农的信息熵作为一种统计量度，用于系统地评估偶然性来源的强度，这是识别偶然性来源的重要组成部分。简而言之，熵越大，强度越大。这在经验上也很重要，因为分子、突变和复制研究通常包含足够的频率或概率数据来计算熵。通过这种方式，权变理论家可以评估现实世界案例中权变源的强度。此外，概率概念还为偶然性来源的相反提供了概念空间：“方向性来源”，这应该被承认，